Literature DB >> 23290926

Long-term evaluation of a 4-class imagery-based brain-computer interface.

Elisabeth V C Friedrich1, Reinhold Scherer, Christa Neuper.   

Abstract

OBJECTIVE: The study aimed to improve brain-computer interface (BCI)-usability by using distinct control strategies and evaluating performance, brain activity and psychological variables on a long-term basis over several months.
METHODS: Fourteen able-bodied users participated in 10 sessions, plus a follow-up session. Users were trained to control an EEG-based 4-class BCI with the mental tasks, word association, mental subtraction, spatial navigation, and motor imagery.
RESULTS: Eight users reached mean accuracies of 61-72% and managed to control all 4 classes above chance in single-sessions. Performance and brain patterns stayed stable over 10 weeks without training. Motor imagery showed the best performance and most distinct brain patterns. Participants' fear of incompetence decreased while the quality of their imagery and task ease increased over sessions. The evaluation of feedback differed between tasks and correlated with performance.
CONCLUSION: Users can control a real-time 4-class BCI, driven by distinct mental tasks, with stable performance over months. However, general performance was rather low for effective BCI control in daily life. Possibilities for future optimizations to increase performance are discussed. SIGNIFICANCE: The evaluation of alternatives to motor imagery, long-term BCI use, and psychological variables is important to improve usability for mental imagery-based BCIs.
Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2013        PMID: 23290926     DOI: 10.1016/j.clinph.2012.11.010

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  13 in total

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2.  Evaluating the perspectives of those with severe physical impairments while learning BCI control of a commercial augmentative and alternative communication paradigm.

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3.  Learning to modulate one's own brain activity: the effect of spontaneous mental strategies.

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4.  Individually adapted imagery improves brain-computer interface performance in end-users with disability.

Authors:  Reinhold Scherer; Josef Faller; Elisabeth V C Friedrich; Eloy Opisso; Ursula Costa; Andrea Kübler; Gernot R Müller-Putz
Journal:  PLoS One       Date:  2015-05-18       Impact factor: 3.240

5.  Enhanced performance by time-frequency-phase feature for EEG-based BCI systems.

Authors:  Baolei Xu; Yunfa Fu; Gang Shi; Xuxian Yin; Zhidong Wang; Hongyi Li; Changhao Jiang
Journal:  ScientificWorldJournal       Date:  2014-06-17

6.  The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications.

Authors:  Andrea Kübler; Elisa M Holz; Angela Riccio; Claudia Zickler; Tobias Kaufmann; Sonja C Kleih; Pit Staiger-Sälzer; Lorenzo Desideri; Evert-Jan Hoogerwerf; Donatella Mattia
Journal:  PLoS One       Date:  2014-12-03       Impact factor: 3.240

7.  An approach to improve the performance of subject-independent BCIs-based on motor imagery allocating subjects by gender.

Authors:  Jessica Cantillo-Negrete; Josefina Gutierrez-Martinez; Ruben I Carino-Escobar; Paul Carrillo-Mora; David Elias-Vinas
Journal:  Biomed Eng Online       Date:  2014-12-04       Impact factor: 2.819

8.  Mental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces.

Authors:  Hubert Banville; Rishabh Gupta; Tiago H Falk
Journal:  Comput Intell Neurosci       Date:  2017-10-18

9.  Whatever works: a systematic user-centered training protocol to optimize brain-computer interfacing individually.

Authors:  Elisabeth V C Friedrich; Christa Neuper; Reinhold Scherer
Journal:  PLoS One       Date:  2013-09-23       Impact factor: 3.240

10.  Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design.

Authors:  Fabien Lotte; Florian Larrue; Christian Mühl
Journal:  Front Hum Neurosci       Date:  2013-09-17       Impact factor: 3.169

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